Typically, an image of a region or scene is produced in order to analyze it and extract desired data therefrom. In medical applications, for example, a probe captures images of a region of interest within a patient's body and image data is used for detection of anomalies, such as unhealthy tissue and polyps. In some other applications, image data is inspected to detect anomalies, such as fire, smoke, or pollution.
When imaging cluttered scenes in varying conditions (noise, clutter, dynamic range, dynamic motion), it is often difficult to perceive subtle anomalies and irregularities in such imagery. This is especially true in imaging situations where such conditions cannot be controlled in terms of signal to background, signal to noise and signal to clutter.
For example, the diagnostic performance in endoscopy, radiology, and ultrasound applications is often limited by low signal to noise levels. Specifically in endoscopy, tissue irregularities may appear as polyps, inflammations, hyper vascular structures, etc. Such indications may be in the superficial layers of tissue, as well as in deeper layers of tissue, which make them more difficult to visualize and detect.